Baltic Sea Gig

CENTRAL BALTIC LAke GIG – PHYTOLANKTON

1. Methods and required BQE parameters

Member State / Full BQE method / Biomass / Taxonomic composition and abundance / Frequency and intensity of algal blooms / Combination rule of metrics
BE-FL / Yes / Biomass (chlorophyll a) / Relative proportion of cyanobacteria / Bloom metric is included as proportion of cyanobacteria are included as a metric and intensity is measured by chlorophyll a / Worst metric score
BE-W / No natural lakes
DK / (Yes draft method) / Biomass (chlorophyll a) / Draft Metric Indicator species and biovolume cyanobacteria / Draft metric will contain a bloom metric is included as biomass of cyanobacteria are included as a metric together with chlorophyll a / Weighted average using a score
EE / Yes / Chlorophyll a / Phytoplankton compound quotient, Pielou's index of evenness
Description of communities / Bloom metric is assessed using evenness and community description which includes cyanobacteria / Avg metric scores
FR / Yes / MBA biomass metric based on Chl-a / MCS specific composition metric / Cyanobacteria are indirectly assessed as the MCS composition metric is indicative of elevated levels of cyanobacteria as these taxa all have low MCS scores / Weighted average of the metric
DE / Yes / Chlorophyll a, Total biovolume , maximum biovolume / Algal classes, PTSI (Phytoplankton-Taxa-Seen-Index) / Cyanobacteria blooms are assessed. Intensity is assessed using biomass and maximum chlorophyll. In addition cyanobacteria have high scores in the indicator taxa (PTSI) / Weighted average metric scores
IE / Yes / Chlorophyll a / IPI index / Two summer samples of chlorophyll a are scored per year (n = 6 per reporting period) in one of the metrics and this may reflect blooms. The abundance of bloom forming cyanobacteria are also assessed twice per year / Average of the two normalised EQRs
LT / Yes / Annual mean concentration of Chl-a / Relative proportions of Cyanobacteria, Bacillariophyta and Chrysophyta / Intensity of blooms are assessed using maximum of chlorophyll a. Also total biovolume and the proportion of cyanobacteria are included as a metric / Avg of metric scores
LV / Yes / Chlorophyll a / Phytoplankton compound quotient, Pielou's index of evenness
Description of communities / Bloom metric is assessed using evenness and community description which includes cyanobacteria / Avg metric scores
NL / Yes / Chlorophyll a / Metric species composition: metric based on algae blooms / Bloom metric is based on list of nuisance species each with a threshold value for cell density and an associated EQR value / Avg metric scores
PL / Yes / Chlorophyll a
Total biomass / Relative proportion of Cyanobacteria / Biomass and the propotion of cyanobacteria are measured directly. / Avg metric scores
UK current method / Yes / Chlorophyll a / Relative proportion of nuisance Cyanobacteria / Use the proportion of cyanobacteria are assessed. Intensity is measured using chlorophyll a / Worst metric score
UK proposed method / Yes / Chlorophyll a / Plankton Trophic Index / Cyanobacteria are indirectly assessed as the PTI composition metric is indicative of elevated levels of cyanobacteria as these taxa all have high PTI scores / Avg metric scores

Explanations : why frequency and intensity of algal blooms are not covered ?

All member states have metrics that detect elevated levels of cyanobacteria which are generally regarded as indicators of algal blooms.

2. National reference conditions

Member State / Methodology used to derive the reference conditions
BE-FL / Expert knowledge for taxonomic metric, chlorophyll from Intercalibration phase 1(based on GIG reference sites
BE-W / Not relevant because all the "lakes" in Wallonia are HMWB
DK / Reference condition is derived from the Intercalibration results (based on GIG reference sites), Expert knowledge for taxonomic metric
EE / Existing near-natural reference sites, expert knowledge, historical data, least disturbed conditions, modelling (extrapolating model results), Reference condition for chlorophyll is derived from the Intercalibration results (based on GIG reference sites)
FR / For chl-a (MBA): RC are site specific, based on a mathematical model between chl-a and mean depth,
For composition metric (MCS): RC are specific per macro lake type, based on ref sites (median value of MCS on ref site per macro lake type) or site specific (when not enough ref sites in macro lake type), based on a mathematical model (regression with TP)
DE / Existing near-natural reference sites and palaeolimnological studies, Reference condition for chlorophyll is derived from the Intercalibration results (based on GIG reference sites)
IE / Existing near-natural reference sites, selected by expert opinion and also through palaeolimnological validation. LCB1 reference for chlorophyll taken from phase 1 IC results. Reference condition for LCB2 taken from combination of expert judgement and near-natural reference sites.
LT / Existing near-natural reference sites, expert knowledge, historical data, least disturbed conditions (to be checked)
LV / Existing near-natural reference sites, expert knowledge, adopted from EE method
NL / Expert knowledge, historical data, least disturbed conditions, modeling (extrapolating model results);
no actual existing natural sites in lakes, reference for chlorophyll taken from phase 1 IC results
PL / Existing near-natural reference sites, expert knowledge, least disturbed conditions, reference for chlorophyll taken from phase 1 IC results
UK / Existing near-natural reference sites, expert knowledge, modeling (extrapolating model results), reference for chlorophyll taken from phase 1 IC results

3. National boundary setting

Member State / Methodology used to set class boundaries
BE-FL / Chl-a boundaries taken from IC (based on species composition shift, secondary effects of eutrophication and compared with equidistant division of EQR gradient), % Cyano – expert judgement
BE-W / No natural lakes
DK / Boundaries taken from the Intercalibration results (based on species composition shift, secondary effects of eutrophication and compared with equidistant division of EQR gradient). Draft taxonomic metric boundaries derived using expert judgement
EE / Based on the biological response to the anthropogenic pressure. GM boundary: break point where the share of tolerant and sensitive species is more or less equal.
FR / MBA: Boundary value H/G is the Prediction Interval of 90th % of the model. Other boundaries are based on the pressure-impact model with log(TP), equal size classes (same distance as between ref and H/G limit).
MCS: boundary value H/G is the 95th % of the distribution on ref sites or the prediction interval of 95th % of the model with log(TP) when not enough ref sites in the macro lake type. Other boundaries are based on the pressure-impact model with log (TP), equal size classes (same distance as between ref and H/G limit).
DE / Boundaries set using deviations from the reference status along the scale of the German LAWA-Index and a TP-derived Index and expert judgment, adjusted by the Intercalibration exercise. Boundaries selected using discontinuities along a pressure gradient
IE / Using discontinuities in the relationship of anthropogenic pressure and the biological response (breakpoints in species composition changes and secondary effects)
LT / For taxonomic composition and chlorophyll a, boundaries were equal division of the EQR gradient.
LV / Taken from the EE method, compared with LV data.
NL / Chl-a boundaries taken from the Intercalibration results (based on species composition shift, secondary effects of eutrophication and compared with equidistant division of EQR gradient), species composition metric threshold values set by expert judgement, linked to equal EQR thresholds (0.2,0.4,0.6,0.8)
PL / Correlation between TP, chlorophyll a, SD and biomass following Carlson`s procedure. Carlson`s index value = 70 was treated as poor/bad boundary. The other boundaries were established based on the frequency of particular values within earlier adopted chlorophyll a classification system.
UK / Chl-a boundaries taken from the Intercalibration results (based on species composition shift, secondary effects of eutrophication and compared with equidistant division of EQR gradient) Percentage of cyanobacteria boundaries set from expert judgement based on conclusions from NGIG phase 1 IC work. Boundaries for proposed new PTI metric based on proportion of sensitive and tolerant taxa

4. Pressures-response relationships

Pressures addressed by the MS assessment methods

Member State / Metrics tested / Pressure / Pressure indicators / Strenght of relationship
BE-FL / Chl-a / EU / TP, TN / Regression R2=0.78 for TP, 0.58 for TN, from 0.52 to 0.81 for types (all GIG common dataset, > 1000 lakes)
BE-W / % Cyano / EU / TP / Spearman correlation TP 0.44
Non-parametric quantile regressions sign for quantiles 0.50, 0.75, 0.90 and 0.95 (WISER common dataset, 602 lakes CB, 6 BE)
DK / Chl-a / EU / TP, TN / Regression R2=TP 0.78, TN 0.58, TN and TP 0.77 from 0.52 to 0.81 for types (all GIG common dataset, > 1000 lakes)
EE / Multimetrics / EU / Catchment index* / Regression R2=0,53, p<0.00001
FR / IPLAC (multimetric) / EU / TP / Regression R2 0.62 (n=112 FR and 22 DE and AT)
DE / Multimetric PSI / EU / TP, LAWA index (incl chl-a, TP, SD) / Correlation R to TP: 0.82 for LAL3 and LAL4, 0.67 LCB1 and 0.48 LCB2, to LAWA index 0.90 LCB1 and 0.91 LCB2
DE / Total biovolume, Algal classes, PTSI / EU / TP / Correlation R ranging from 0.55 to 0.77 for LAL3, 0.70 to 0.85 for LAL4, 0.42 to 0.82 for LCB1, 0.28 to 0.51 for LCB2
IE / Chl-a / EU / TP, TN / Regression R2=0.78 for TP, 0.58 for TN, from 0.52 to 0.81 for types (all GIG common dataset, > 1000 lakes)
IE / IPI index / EU / TP / Regression R2 = 0.67 (p <0.0001, n=129). For independent data set: R2 = 0.62 (p <0.0001, n=30)
LT / Annual mean chl-a / EU / TP, TN / Lakes < 3m deep (n=30) TN 0.2 and TP 0.6 (p<0.05); 3 -9m deep (n=44): TN 0.6 and TP 0.4; lakes > 9m deep (n=26): TN 0.3 and TP 0.2 (all p<0.05)
LT / Max chl-a: / EU / TP, TN / Lakes < 3m (n=30) TN 0.3 and TP 0.4; 3 - 9m deep (n=44): TN 0.4 and TP 0.5; lakes > 9 m (n=26): TN 0.4 and TP 0.1 (all p<0.05)
LT / % Cyano / EU / TP / Spearman correlation TP 0.44
Non-parametric quantile regressions sign for quantiles 0.50, 0.75, 0.90 and 0.95 (WISER common dataset, 602 lakes CB, 6 BE)
LT / % Bacillario+ Chrysophyta / EU / TP / tested but not sign relationships found (n=26)
LV / Chl-a / EU / TP, TN / Regression R2=0.78 for TP, 0.58 for TN, from 0.52 to 0.81 for types (all GIG common dataset, > 1000 lakes)
LV / Evenness index / EU / BV / Correlation R=0.41 (p< 0.001)
LV / PCQ / EU / BV, chl / Correlation - BV R=0.18 , PCQ-chl 0.40 (1st type), 0.34 (2nd type), p< 0.01
LV / Community description / EU / BV / Correlation: com description -BV R=0.36, p< 0.01
NL / Chl-a / EU / TP, TN / Regression R2=0.78 for TP, 0.58 for TN, from 0.52 to 0.81 for types (all GIG common dataset, > 1000 lakes)
NL / Metric species composition / EU / TP, TN, chl-a, chl-a:P / Correlations: For M11/M14 and M25/M27 (depth 1.5 m) EQR -TP 0.48-0.55, TN 0.44-0.73, chl-a 0.67-0.81, chl-a:P 0.37-0.53, for M16/M20/M21 (depth 6m) chl-a 0.69, chla:P 0.68
PL / Chl-a / EU / TP, TN / Correlation TP 0.64, TN 0.40 (all p <0.05), n=39
PL / Biomass of phytoplankton / EU / TP, TN / Correlation TP 0.55, TN 0.44 (all p <0.05), n=39
PL / % Cyano / EU / TP, TN / Correlation TP 0.49, TN 0.39 (all p <0.05), n=39
UK / Chl-a / EU / TP, TN / Regression R2=0.78 for TP, 0.58 for TN, from 0.52 to 0.81 for types (all GIG common dataset, > 1000 lakes)
UK / % Cyano / EU / TP / Spearman correlation TP 0.44
Non-parametric quantile regressions sign for quantiles 0.50, 0.75, 0.90 and 0.95 (WISER dataset, 602 lakes CB )
UK proposed metric / PTI metric / EU / TP / Correlation TP 0.59 (p<0.001, n=?? )

*Inhabitant density per water volume of the lake + % of natural and agricultural land use + number of domestic animals per water volume + secondary pollution